<![CDATA[Generation Z refers to individuals born approximately between 1997 and 2012, who are currently growing and developing alongside the rapid advancement of Artificial Intelligence (AI) technology. Although this technology offers various advantages, several issues have emerged regarding students' learning behavior. In this context, learning motivation may serve as a mediating factor linking students' academic performance with their use of AI, especially in cases such as underestimating problems, developing dependency, and experiencing a decline in critical thinking, despite the many educational benefits AI offers. This study aims to analyze the effect of Artificial Intelligence (AI) usage on students’ academic performance and to examine the role of learning motivation as a mediating variable in the relationship between AI usage and learning outcomes. Using a quantitative survey approach, data were collected through questionnaires distributed to 68 respondents and analyzed using the Structural Equation Modeling (SEM) method. The independent variable is the use of AI, measured through the Technology Acceptance Model (TAM); the mediating variable is learning motivation; and the dependent variable is academic performance, measured by students’ Grade Point Average (GPA).The findings indicate that AI usage does not directly influence students’ academic performance. However, learning motivation acts as a full mediator in the relationship between AI usage and academic achievement. The lack of significant direct influence from AI is attributed to the fact that its effectiveness largely depends on students’ motivation and readiness to access and utilize the technology optimally. Therefore, learning motivation serves as a full mediator, as the influence of AI on academic performance only emerges when learning motivation increases.]]>
